A Survival-Related Competitive Endogenous RNA Network of Prognostic lncRNAs, miRNAs, and mRNAs in Wilms Tumor.
Ontology highlight
ABSTRACT:
SUBMITTER: Liu H
PROVIDER: S-EPMC7953909 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BACKGROUND:Competitive endogenous RNAs (ceRNAs) have revealed a new mechanism of interaction between RNAs. However, an understanding of the ceRNA regulatory network in Wilms tumour (WT) remains limited. METHODS:The expression profiles of mRNAs, miRNAs and lncRNAs in Wilms tumour samples and normal samples were obtained from the Therapeutically Applicable Research to Generate Effective Treatment (TARGET) database. The EdgeR package was employed to identify differentially expressed lncRNAs, miRNAs and mRNAs. Functional enrichment analyses via the ClusterProfile R package were performed, and the lncRNA-miRNA-mRNA interaction ceRNA network was established in Cytoscape. Subsequently, the correlation between the ceRNA network and overall survival was analysed. RESULTS:A total of 2037 lncRNAs, 154 miRNAs and 3609 mRNAs were identified as differentially expressed RNAs in Wilms tumour. Of those, 205 lncRNAs, 26 miRNAs and 143 mRNAs were included in the ceRNA regulatory network. The results of Gene Ontology (GO) analysis revealed that the differentially expressed genes (DEGs) were mainly enriched in terms related to response to mechanical stimuli, transcription factor complexes, and transcription factor activity (related to RNA polymerase II proximal promoter sequence-specific DNA binding). The results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the DEGs were mainly enriched in pathways related to the cell cycle. The survival analysis results showed that 16 out of the 205 lncRNAs, 1 out of 26 miRNAs and 5 out of 143 mRNAs were associated with overall survival in Wilms tumour patients (P?<?0.05). CONCLUSIONS:CeRNA networks play an important role in Wilms tumour. This finding might provide effective, novel insights for further understanding the mechanisms underlying Wilms tumour.
| S-EPMC6915924 | biostudies-literature
Project description:BackgroundType 1 diabetes (T1D, named insulin-dependent diabetes) has a relatively rapid onset and significantly decreases life expectancy. This study is conducted to reveal the long non-coding RNA (lncRNA)-microRNA (miRNA)-mRNA regulatory axises implicated in T1D.MethodsThe gene expression profile under GSE55100 (GPL570 and GPL8786 datasets; including 12 T1D samples and 10 normal samples for each dataset) was extracted from Gene Expression Omnibus database. Using limma package, the differentially expressed mRNAs (DE-mRNAs), miRNAs (DE-miRNAs), and lncRNAs (DE-lncRNAs) between T1D and normal samples were analyzed. For the DE-mRNAs, the functional terms were enriched by DAVID tool, and the significant pathways were enriched using gene set enrichment analysis. The interactions among DE-lncRNAs, DE-miRNAs and DE-mRNAs were predicted using mirwalk and starbase. The lncRNA-miRNA-mRNA interaction network analysis was visualized by Cytoscape. The key genes in the interaction network were verified by quantitatively real-time PCR.ResultsIn comparison to normal samples, 236 DE-mRNAs, 184 DE-lncRNAs, and 45 DE-miRNAs in T1D samples were identified. For the 236 DE-mRNAs, 16 Gene Ontology (GO)_biological process (BP) terms, four GO_cellular component (CC) terms, and 57 significant pathways were enriched. A network involving 36 DE-mRNAs, 8 DE- lncRNAs, and 15 DE-miRNAs was built, such as TRG-AS1-miR-23b/miR-423-PPM1L and GAS5-miR-320a/miR-23b/miR-423-SERPINA1 regulatory axises. Quantitatively real-time PCR successfully validated the expression levels of TRG-AS1- miR-23b -PPM1L and GAS5-miR-320a- SERPINA1.ConclusionTRG-AS1-miR-23b-PPM1L and GAS5-miR-320a-SERPINA1 regulatory axises might impact the pathogenesis of T1D.
| S-EPMC7852109 | biostudies-literature
Project description:Wilms' tumor (WT) is one of the most common types of renal carcinoma in children. The aim of the present study was to construct a competitive endogenous RNA (ceRNA) regulation network and explore novel prognostic biomarkers for WT. The expression profiles were downloaded from The Cancer Genome Atlas database to identify differentially expressed RNAs (DERNAs). Based on the interactions between microRNAs (miRNAs) and mRNAs/long non-coding RNAs (lncRNAs), a ceRNA network was constructed. Functional enrichment analyses were subsequently conducted to explore the functions of the ceRNA-associated DEmRNAs. Survival analysis was performed to screen for prognosis-associated RNAs and the ?2 test was used to assess the associations between prognosis-associated RNA expression and histology classification/clinical staging. The present study identified 1,784 lncRNAs, 114 miRNAs and 3,337 mRNAs, which were abnormally expressed in WT compared with that in normal samples. By prediction, pairing and network analysis, a ceRNA network consisting of 38 DElncRNAs, 18 DEmiRNAs and 99 DEmRNAs was established. These DEmRNAs were significantly enriched in pathways associated with the occurrence and development of WT. By combining the expression data with survival analysis, seven prognosis-associated RNAs were identified (P<0.05). Of these seven RNAs, two (zinc finger and BTB domain containing 4; and deleted in lymphocytic leukemia 2) were significantly associated with clinical staging and histology classification. Lastly, the expression levels of the seven RNAs were verified in the Gene Expression Omnibus database. The present study revealed that 7 RNAs might be considered as novel prognostic biomarkers and potential treatment targets for therapy in WT. In addition, the ceRNA regulation network could provide novel strategies for further studies on lncRNAs and miRNAs in WT.
| S-EPMC7202313 | biostudies-literature
Project description:The competing endogenous RNA (ceRNA) network is crucial for the development and progression of tumors, including non?small cell lung cancer (NSCLC). However, what type of ceRNA network regulates NSCLC has not been clarified. The present study aimed to elucidate the long non?coding RNA (lncRNA)/microRNA (miRNA)/mRNA ceRNA network in NSCLC, particularly for the significance of lncRNAs in NSCLC. NSCLC?specific differentially expressed lncRNAs, miRNAs and mRNAs in the Cancer Genome Atlas (TCGA) were analyzed and their relationship was analyzed by a ceRNA network. Their potential functions of differentially expressed mRNAs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Furthermore, the expression levels of four selected lncRNAs in TCGA were determined and their associated survival of patients was examined. In addition, the expression profiles of these four lncRNAs in 48 NSCLC specimens and cell lines, their cellular distribution and associated clinical parameters were examined. We successfully constructed a ceRNA network, including 113 lncRNAs, 12 miRNAs and 36 mRNAs differentially expressed between NSCLC and non?tumor tissues. LINC00525, MED4?AS1, STEAP2?AS1 and SYNPR?AS1 lncRNAs were selected and validated for their association with the survival of NSCLC patients. The expression of these lncRNAs was upregulated in 48 NSCLC tissues and was varying in NSCLC cells. While LINC00525 was mainly expressed in the cytoplasm, MED4?AS1 was in both the nucleus and cytoplasm of A549 cells. In addition, the expression of LINC00525 was significantly associated with smoking history (P<0.05); MED4?AS1 was significantly associated with women, poor differentiation and lymph node metastasis (P<0.05); STEAP2?AS1 was significantly associated with women (P<0.01); and SYNPR?AS1 was significantly associated with women and adenocarcinoma (P<0.05). These lncRNAs may be valuable biomarkers for prognosis of NSCLC and the ceRNA network may provide new insights in the pathogenesis of NSCLC.
| S-EPMC6859443 | biostudies-literature
Project description:Long non-coding RNAs (lncRNAs) are key regulators of a range of human diseases, including various cancers, with multiple previous studies having explored lncRNA dysregulation in the context of gastric cancer (GC). The present study sought to expand upon these previous results by downloading lncRNA, mRNA, and microRNA (miRNA) expression profiles derived from 180 GC tissues and 24 normal control tissues within the Cancer Genome Atlas (TCGA) database. These datasets were then interrogated to identify GC-related differentially expressed (DE) RNAs (|fold change| ≥ 2, FDR< 0.01), leading to the identification of 1946 DE lncRNAs, 123 DE miRNAs, and 3159 DE mRNAs. These results were then used to generate a putative GC-related competitive endogenous RNA (ceRNA) network composed of 131 lncRNAs, 9 miRNAs, and 78 mRNAs. Subsequent survival analyses based upon this network revealed 17 of these lncRNAs to be significantly associated with GC patient survival (P < 0.05). Further multivariable Cox regression and lasso analyses allowed for the construction of an 8-lncRNA risk score that was able to effectively predict GC patient survival with good discriminative ability. The Kaplan-Meier Plotter database further confirmed that network hub genes that were related to these 8 lncRNAs were associated with GC patient prognosis (P < 0.05). As the ceRNA network in the present study was constructed with a focus on both disease stage and differential gene expression, it represents a key resource that will offer valuable insights into the mechanistic roles of ceRNA pathways in GC development and progression.
| S-EPMC7235626 | biostudies-literature
Project description:The aim of the present study is to construct a competitive endogenous RNA (ceRNA) regulatory network by using differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in patients with hepatocellular carcinoma (HCC), and to construct a prognostic model for predicting overall survival (OS) of HCC patients. Differentially expressed lncRNAs, miRNAs, and mRNAs were explored between HCC tissues and normal liver tissues. A prognostic model was built for predicting OS of HCC patients and receiver operating characteristic curves were used to evaluate the performance of the prognostic model. There were 455 differentially expressed lncRNAs, 181 differentially expressed miRNAs, and 5035 differentially expressed mRNAs. A ceRNA regulatory network was constructed based on 43 lncRNAs, 37 miRNAs, and 105 mRNAs. Eight mRNA biomarkers (H2AFX, SQSTM1, ITM2A, PFKP, TPD52L1, ACSL4, STRN3, and CPEB3) were identified as independent risk factors by multivariate Cox regression and were used to develop a prognostic model for OS. The C-indexes in the model group were 0.776 (95% confidence interval [CI], 0.730-0.822), 0.745 (95% CI, 0.699-0.791), and 0.789 (95% CI, 0.743-0.835) for 1-, 3-, and 5-year OS, respectively. The current study revealed potential molecular biological regulation pathways and prognostic biomarkers by the ceRNA regulatory network. A prognostic model based on prognostic mRNAs in the ceRNA network might be helpful to predict the individual mortality risk for HCC patients. The individual mortality risk calculator can be used by visiting the following URL: https://zhangzhiqiao.shinyapps.io/Smart_cancer_predictive_system_HCC/.
| S-EPMC6726690 | biostudies-literature
Project description:The objective of this study was to construct a competitive endogenous RNA (ceRNA) regulatory network using differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in patients with triple-negative breast cancer (TNBC) and to construct a prognostic model for predicting overall survival (OS) in patients with TNBC. Differentially expressed lncRNAs, miRNAs, and mRNAs in TNBC patients from the TCGA and Metabric databases were examined. A prognostic model based on prognostic scores (PSs) was established for predicting OS in TNBC patients, and the performance of the model was assessed by a recipient that operated on a distinctive curve. A total of 874 differentially expressed RNAs (DERs) were screened, among which 6 lncRNAs, 295 miRNAs and 573 mRNAs were utilized to construct targeted and coexpression ceRNA regulatory networks. Eight differentially expressed genes (DEGs) associated with survival prognosis, DBX2, MYH7, TARDBP, POU4F1, ABCB11, LHFPL5, TRHDE and TIMP4, were identified by multivariate Cox regression and then used to establish a prognostic model. Our study shows that the ceRNA network has a critical role in maintaining the aggressiveness of TNBC and provides comprehensive molecular-level insight for predicting individual mortality hazards for TNBC patients. Our data suggest that these prognostic mRNAs from the ceRNA network are promising therapeutic targets for clinical intervention.
| S-EPMC8232227 | biostudies-literature
Project description:Wilms tumor (WT) is the most common malignant renal neoplasm in children; however, the underlying molecular mechanisms are not well understood. According to the competing endogenous RNA (ceRNA) theory, long non‑coding RNAs (lncRNAs) can regulate the expression of target genes by adsorbing microRNAs (miRNAs/miRs). However, the role of lncRNAs in WT has not been fully elucidated. The aim of the present study was to construct a ceRNA network to identify the potential lncRNAs involved in WT. The expression profiles of lncRNAs, miRNAs and mRNAs in 120 WT and six normal tissues were obtained from the Therapeutically Applicable Research to Generate Effective Treatments database. A total of 442 lncRNAs, 214 miRNAs and 4,912 mRNAs were identified as differentially expressed in WT and were enriched in 472 Gene Ontology terms (355 biological processes, 89 cellular components and 29 molecular functions) and 18 Kyoto Encyclopedia of Genes and Genomes pathways. A lncRNA‑miRNA‑mRNA ceRNA network of WT consisting of with 32 lncRNAs, 14 miRNAs and 158 mRNAs was constructed, based on the bioinformatics analysis of the miR target prediction database and the miRNAcode, miRTarBase and TargetScan databases. Subsequently, three lncRNAs, three miRNAs and 17 mRNAs, which had a significant effect on the overall survival rate of patients with WT, were identified based on the survival analysis. The three lncRNAs were also differentially expressed in the late and early stages of WT and were validated using the GSE66405 dataset obtained from the Gene Expression Omnibus database. In conclusion, the present study generated a specific lncRNA‑related ceRNA network of WT, which may provide a novel perspective on the molecular mechanisms underlying the progression and prognosis of the disease.
| S-EPMC7252721 | biostudies-literature
Project description:BACKGROUND The aims of this study were to use RNA expression profile bioinformatics data from cases of thyroid cancer from the Cancer Genome Atlas (TCGA), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Gene Ontology (GO) databases to construct a competing endogenous RNA (ceRNA) network of mRNAs, long noncoding RNAs (lncRNAs), and microRNAs (miRNAs). MATERIAL AND METHODS TCGA provided RNA profiles from 515 thyroid cancer tissues and 56 normal thyroid tissues. The DESeq R package analyzed high-throughput sequencing data on differentially expressed RNAs. GO and KEGG pathway analysis used the DAVID 6.8 and the ClusterProfile R package. Kaplan-Meier survival statistics and Cox regression analysis were performed. The thyroid cancer ceRNA network was constructed based on the miRDB, miRTarBase, and TargetScan databases. RESULTS There were 1,098 mRNAs associated with thyroid cancer; 101 mRNAs were associated with overall survival (OS). Multivariate analysis developed a risk scoring system that identified seven signature mRNAs, with a discriminative value of 0.88, determined by receiver operating characteristic (ROC) curve analysis. A ceRNA network included 13 mRNAs, 31 lncRNAs, and seven miRNAs. Four out of the 31 lncRNAs and all miRNAs were down-regulated, and the remaining RNAs were upregulated. Two lncRNAs (MIR1281A2HG and OPCML-IT1) and one miRNA (miR-184) were significantly associated with OS in patients with thyroid cancer. CONCLUSIONS Differential RNA expression profiling in thyroid cancer was used to construct a ceRNA network of mRNAs, lncRNAs, and miRNAs that showed potential in evaluating prognosis.
| S-EPMC6380385 | biostudies-literature
Project description:BackgroundLong noncoding RNAs (lncRNAs) play a role in the formation, development, and prognosis of various cancers. Our study aimed to identify prognostic-related lncRNAs in lung squamous cell carcinoma (LUSC), which may provide new perspectives for individualized treatment of patients.Materials and methodsThe RNA sequencing (lncRNA, microRNA (miRNA), mRNA) data and clinical information related to LUSC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed RNA sequences were used to construct the competitive endogenous RNA (ceRNA) network. In present study, we mainly used two prognostic verification methods, Cox analysis and survival analysis, to identify the prognostic relevance of specific lncRNAs and construct prognostic model of lncRNA.ResultsDatasets on 551 samples of lncRNA and mRNA and 523 miRNA samples were retrieved from the TCGA database. Analysis of the normal and LUSC samples identified 170 DElncRNAs, 331 DEmiRNAs, and 417 DEmRNAs differentially expressed RNAs. The ceRNA network contained 27 lncRNAs, 43 miRNAs, and 11 mRNAs. Furthermore, we identified seven specific lncRNAs (ERVH48-1, HCG9, SEC62-AS1, AC022148.1, LINC00460, C5orf17, LINC00261) as potential prognostic factors after correlation analysis, and five of the seven lncRNAs (AC022148.1, HCG9, LINC00460, C5orf17, LINC00261) constructed a prognostic model of LUSC.ConclusionIn present study, we identified seven lncRNAs in the ceRNA network that are associated with potential prognosis in LUSC patients, and constructed a prognostic model of LUSC which can be used to assess the prognosis risk of clinical patients. Further biological experiments are needed to elucidate the specific molecular mechanisms underlying them.
| S-EPMC6753923 | biostudies-literature